Disaggregating Health Differences and Disparities With Machine Learning and Observed-to-expected Ratios: Application to Major Lower Limb Amputation.

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Bibliographic Details
Title: Disaggregating Health Differences and Disparities With Machine Learning and Observed-to-expected Ratios: Application to Major Lower Limb Amputation.
Authors: Strassle PD; From the Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD.; Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD., Minc SD; Department of Surgery, Duke University, Durham, NC., Kalbaugh CA; Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN., Donneyong MM; Pharmacy Practice and Sciences, College of Pharmacy, The Ohio State University, Columbus, OH., Ko JS; Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD.; Department of Surgery, University of California Los Angeles, Los Angeles, CA., McGinigle KL; Division of Vascular Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Source: Epidemiology (Cambridge, Mass.) [Epidemiology] 2025 Nov 01; Vol. 36 (6), pp. 841-848. Date of Electronic Publication: 2025 Jul 07.
Publication Type: Journal Article
Journal Info: Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 9009644 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1531-5487 (Electronic) Linking ISSN: 10443983 NLM ISO Abbreviation: Epidemiology Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1531-5487
DOI:10.1097/EDE.0000000000001892